Marvin vs Skylos

Marvin and Skylos address opposite ends of the AI lifecycle: generation vs. verification. Marvin is a Python framework that uses decorators like @ai_fn and @ai_classifier to turn plain functions into LLM-powered tools. It supports structured extraction via Pydantic models, agent loops with tool calling, streaming (SSE), and an async-first API. It runs in your environment with caching, rate limiting, and retries. Skylos, conversely, is a static analysis CLI that scans Python code for dead code (functions, imports, classes), security vulnerabilities (SQL injection, secrets like AWS/Stripe keys), and AI-specific defects such as hallucinated imports, phantom calls, and removed security controls. It integrates as a PR gate in GitHub Actions (with a documented secure workflow from May 2026) and supports confidence scoring to reduce noise. Skylos also offers a Cloud workspace for shared triage, while Marvin has none. Both are open-source; Skylos adds a paid tier for cloud features. The feature sets overlap only in that both target Python developers — otherwise they are complementary, not competitive.

Marvin is entirely free and open-source — no paid tiers, no cloud dependency. You run it locally or in your own environment. Skylos is freemium: the CLI is free and works without login for local scans, but the Cloud Workspace costs $9 for 50 credits, which adds stored scan history, PR comments, and Slack/Discord alerts. For teams needing only local or CI-based scanning, Skylos's free tier suffices. Marvin offers no equivalent cloud service, so if you need a managed platform, Skylos's paid tier is the option. However, Skylos's cloud features require uploading code, which may be a concern for some. Both tools are inexpensive: Marvin is free forever, Skylos is free for local use and low-cost for cloud features.